Multiobjective-based concepts to handle constraints in evolutionary algorithms

This paper presents the main multiobjective optimization concepts that have been used in evolutionary algorithms to handle constraints in global optimization problems. A review of some approaches developed under these concepts is provided. Additionally, a comparison of four representative techniques using well-known test functions is shown. Finally, the analysis of the results obtained, based on three main points (quality, consistency and diversity) and some conclusions and future trends are also provided.